Overview
The University of Oxford is inviting applications for a full-time Postdoctoral Research Assistant position in applied machine learning. This role is part of the HumBug project, which focuses on developing advanced mosquito detection systems to enhance understanding of malaria transmission. The successful candidate will join the Machine Learning Research Group within the Department of Engineering Science located in central Oxford.
Background & Relevance
Applied machine learning is a rapidly evolving field that plays a crucial role in various domains, including healthcare and environmental science. The intersection of machine learning with acoustic data analysis and smart sensors is particularly significant for addressing public health challenges, such as malaria. By leveraging innovative detection algorithms and spatio-temporal modelling, researchers can contribute to more effective disease prevention strategies.
Key Details
- Position: Postdoctoral Research Assistant in Applied Machine Learning
- Institution: University of Oxford
- Project: HumBug (http://humbug.ac.uk)
- Duration: Fixed-term for up to 36 months
- Application Deadline: 12:00 midday on Wednesday, 18 September 2019
- Application Link: Application Form
Eligibility & Participation
This opportunity is targeted at individuals who hold a relevant PhD/DPhil or are nearing completion. Candidates should possess a first degree in engineering, physics, computer science, mathematics, statistics, or a related field, with a specialization in probabilistic models. The position is ideal for those who are passionate about applying machine learning techniques to real-world challenges.
Submission or Application Guidelines
To apply for this position, candidates must submit the following materials online:
– A covering letter or supporting statement that includes a brief overview of research interests and how they align with the position
– A CV
– Contact details for two referees
Additional Context / Real-World Relevance
The integration of machine learning with acoustic analysis and smart sensors represents a significant advancement in the fight against malaria. By developing innovative mosquito detection systems, researchers can provide vital insights into the dynamics of disease transmission, ultimately contributing to public health initiatives and improving outcomes in affected regions.
Conclusion
This postdoctoral position at the University of Oxford offers a unique opportunity to engage in impactful research at the intersection of machine learning and public health. Interested candidates are encouraged to apply and contribute to this vital area of study, helping to pave the way for innovative solutions in malaria detection and prevention.
Category: PhD & Postdoc Positions
Tags: applied machine learning, acoustic data analysis, smart sensors, spatio-temporal modelling, malaria research, detection algorithms, software engineering, probabilistic models, University of Oxford
